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Lead AI Engineer - Machine Learning

ZS's Scaled AI practice is part of ZS rich and advanced AI ecosystem. We are building next generation AI based analytics products, focused on creatin innovative machine learning, and engineering capabilities. Our team comprises of Data Scientists, ML/Full Stack Engineers, UI Developers, Product/ Program managers and QA testers working together to build products which offers unique analytical solutions to our clients.

Responsibilities

- Build, refine, and use ML engineering platforms and components.
- Scale machine learning algorithms to work on massive data sets and meet strict SLAs.
- Build and orchestrate model pipelines, including feature engineering, inferencing, and continuous model training.
- Implement ML Ops, including model KPI measurements, tracking, model drift, and model feedback loop.
- Collaborate with client-facing teams to understand business context at a high level and contribute to technical requirement gathering.
- Implement basic features aligning with technical requirements.
- Write production-ready code that is easily testable, understood by other developers, and accounts for edge cases and errors.
- Ensure the highest quality of deliverables by following architecture/design guidelines, coding best practices, and conducting periodic design/code reviews.
- Write unit tests as well as higher-level tests to handle expected edge cases and errors gracefully, along with happy paths.
- Use bug tracking, code review, version control, and other tools to organize and deliver work.
- Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues, and dependencies.




- Consistently contribute to researching and evaluating the latest architecture patterns/technologies through rapid learning, conducting proof-of-concepts, and creating prototype solutions.

Qualifications

- A master’s or bachelor’s degree in Computer Science or a related field from a top university.
- 5+ years of hands-on experience in ML development.
- Positive fundamentals of machine learning.
- Strong programming expertise in Python, PySpark/Scala.
- Expertise in crafting ML models for high performance and scalability.
- Experience in implementing feature engineering, inferencing pipelines, and real-time model predictions.
- Experience in ML Ops to measure and track model performance, with experience working with MLFlow.
- Experience with Spark or other distributed computing frameworks.
- Experience in ML platforms like SageMaker and Kubeflow.
- Experience with pipeline orchestration tools such as Airflow.
- Experience in deploying models to cloud services like AWS, Azure, GCP, and Azure ML.
- Expertise in SQL and SQL databases.
- Knowledgeable of core CS concepts such as common data structures and algorithms.
- Collaborate well with teams with different backgrounds, expertise, and functions.

? Job Details Experience5-6 years

Location

GurgaonPuneBengaluru

CountryIndia

CategoryPlatforms and Products

Job TypeFull Time

SalaryNot Disclosed

Posted24-02-2025

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📌 Lead AI Engineer - Machine Learning (Bengaluru)
🏢 Interview Breeze
📍 Bengaluru